Bag of little bootstraps on features for enhancing classification performance

[1]  Bo Meng,et al.  A new modeling method based on bagging ELM for day-ahead electricity price prediction , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[2]  Lars Kai Hansen,et al.  Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Jiawei Han,et al.  Modeling hidden topics on document manifold , 2008, CIKM '08.

[4]  Dianhui Wang,et al.  Extreme learning machines: a survey , 2011, Int. J. Mach. Learn. Cybern..

[5]  F. Götze,et al.  RESAMPLING FEWER THAN n OBSERVATIONS: GAINS, LOSSES, AND REMEDIES FOR LOSSES , 2012 .

[6]  Maryam Mirzaei,et al.  Corporate Default Prediction with AdaBoost and Bagging Classifiers , 2015 .

[7]  Chee Kheong Siew,et al.  Extreme learning machine: Theory and applications , 2006, Neurocomputing.

[8]  Jean-Philippe Vert,et al.  A bagging SVM to learn from positive and unlabeled examples , 2010, Pattern Recognit. Lett..

[9]  Guang-Bin Huang,et al.  Extreme learning machine: a new learning scheme of feedforward neural networks , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[10]  Ru-zhi Xu,et al.  A Short Term Load Forecasting Based on Bagging-ELM Algorithm , 2013 .

[11]  Andrew W. Moore,et al.  Logistic regression for data mining and high-dimensional classification , 2004 .

[12]  Thomas S. Huang,et al.  Graph Regularized Nonnegative Matrix Factorization for Data Representation. , 2011, IEEE transactions on pattern analysis and machine intelligence.

[13]  Giorgio Valentini,et al.  Low Bias Bagged Support Vector Machines , 2003, ICML.

[14]  Bin Linghu,et al.  Constructing effective SVM ensembles for image classification , 2010, 2010 Third International Symposium on Knowledge Acquisition and Modeling.

[15]  Lin Ma,et al.  Empirical analysis of support vector machine ensemble classifiers , 2009, Expert Syst. Appl..

[16]  Johan A. K. Suykens,et al.  EnsembleSVM: a library for ensemble learning using support vector machines , 2014, J. Mach. Learn. Res..

[17]  Purnamrita Sarkar,et al.  A scalable bootstrap for massive data , 2011, 1112.5016.

[18]  Zaiyong Tang,et al.  Ensemble methods in bank direct marketing , 2014, 2014 11th International Conference on Service Systems and Service Management (ICSSSM).

[19]  Tin Kam Ho,et al.  The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Stephen D. Bay Nearest neighbor classification from multiple feature subsets , 1999, Intell. Data Anal..

[21]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[22]  P. N. Suganthan,et al.  Empirical comparison of bagging-based ensemble classifiers , 2012, 2012 15th International Conference on Information Fusion.

[23]  Francis K. H. Quek,et al.  Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets , 2003, Pattern Recognit..

[24]  Fuzhen Zhuang,et al.  Extreme Learning Machine Ensemble Classifier for Large-Scale Data , 2015 .

[25]  M. Mirzaei,et al.  Corporate Default Prediction with Data Mining Techniques , 2015 .

[26]  Jiawei Han,et al.  Regularized locality preserving indexing via spectral regression , 2007, CIKM '07.